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Determinação dos parâmetros do controlador preditivo generalizado com função de pesos variante no tempo através de algoritmos genéticos

机译:遗传算法确定时变权函数的广义预测控制器参数

摘要

The predictive control technique has gotten, on the last years, greater number of adepts in reason of the easiness of adjustment of its parameters, of the exceeding of its concepts for multi-input/multi-output (MIMO) systems, of nonlinear models of processes could be linearised around a operating point, so can clearly be used in the controller, and mainly, as being the only methodology that can take into consideration, during the project of the controller, the limitations of the control signals and output of the process. The time varying weighting generalized predictive control (TGPC), studied in this work, is one more an alternative to the several existing predictive controls, characterizing itself as an modification of the generalized predictive control (GPC), where it is used a reference model, calculated in accordance with parameters of project previously established by the designer, and the application of a new function criterion, that when minimized offers the best parameters to the controller. It is used technique of the genetic algorithms to minimize of the function criterion proposed and searches to demonstrate the robustness of the TGPC through the application of performance, stability and robustness criterions. To compare achieves results of the TGPC controller, the GCP and proportional, integral and derivative (PID) controllers are used, where whole the techniques applied to stable, unstable and of non-minimum phase plants. The simulated examples become fulfilled with the use of MATLAB tool. It is verified that, the alterations implemented in TGPC, allow the evidence of the efficiency of this algorithm
机译:预测控制技术由于易于调整参数,超出了其多输入/多输出(MIMO)系统的概念,非线性模型的应用而在过去几年中获得了更多的应用。过程可以在一个工作点周围线性化,因此可以清楚地用在控制器中,并且主要是因为它是唯一可以在控制器项目期间考虑控制信号和过程输出限制的方法。在这项工作中研究的时变加权广义预测控制(TGPC)是现有的几个预测控制的另一种选择,其特征是对广义预测控制(GPC)的修改,在该模型中,它用作参考模型,根据设计人员先前建立的项目参数以及新功能标准的应用计算得出的结果,将其最小化时将为控制器提供最佳参数。它是遗传算法的技术,用于最小化提出的功能准则,并通过性能,稳定性和鲁棒性准则的应用来寻求证明TGPC的鲁棒性。为了比较TGPC控制器的实现结果,使用了GCP控制器和比例,积分和微分(PID)控制器,其中将全部技术应用于稳定,不稳定和非最小相位设备。通过使用MATLAB工具可以实现模拟示例。验证了在TGPC中实现的变更,为该算法的有效性提供了证据。

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